Wednesday, April 1, 2026

Buddhist and Christian Takes on "Suffering"

Being as how it is Holy Week for Christians, and focused (for some) on the passion (from Latin passio, "suffering"), or intense physical and spiritual sufferings of Jesus Christ between the Last Supper and his death on the Cross, I have been thinking about "suffering" as core theological insights of Buddhism and the Catholic form of Christianity.

Both Catholicism and Buddhism place suffering at the center of their teachings, viewing it as a universal human reality that demands a serious response.

Neither tradition denies the reality of pain, but Catholicism focuses on ways to redeem it while Buddhism seeks to transcend it entirely.

The Buddhist Second Noble Truth locates the origin of suffering in craving (tanha), rooted in ignorance of the three marks of existence: impermanence (anicca), suffering/unsatisfactoriness (dukkha), and no-self (anatta). 

Because all things are conditioned and empty of inherent self, clinging to them inevitably produces suffering.

Psychologist Jordan Peterson has said "there's no difference between being concerned with yourself and being miserable."

That captures much of the Buddhist approach. 

Both traditions insist that suffering is universal and must be faced honestly rather than avoided; both cultivate compassion for all who suffer.

Both emphasize ethical living and mental discipline as essential responses. 

Both promise a final state free from suffering (heaven or nirvana). But it is the understanding of suffering "in the here and now" that is different. 

For the Buddhist, suffering has no divine author or redemptive purpose. It is simply a natural law to be understood and transcended.

Catholics take a "redemptive" view of suffering. Pain is not the issue. It is the potential meaning of the suffering, which can have redemptive value for other humans, in the same way that acts of service (feeding the hungry, clothing the naked, housing the homeless, visiting the sick) help other people. 

Not to get into the weeds theologically, but understanding one's suffering as a communion with God and other people (communion of saints) means that what you suffer, "united" with the suffering of Jesus and others, is a form of prayer for the well-being of others. 

Tuesday, March 31, 2026

Why Market Researchers and Financial Analysts Have Different Takes on SASE

On the surface, it might seem logical that artificial intelligence, as a tool to automate threat detection and replace manual security processes could displace some functions of current threat protection apps, including SASE (Secure Access Service Edge). 


On the other hand, it is pretty hard to find any major industry analyst report that supports that line of thinking. AI represents new attack surfaces, for example, arguably increasing the need for SASE. 


On the other hand, financial analysts seem to universally believe the AI danger to enterprise software is significant. And there’s no absolutely-clear way to know which view is correct. 


There are pros and cons to the argument, as you would guess. 


Pro/Con

Argument

Evidence / Detail

Source

PRO ↓

AI automates threat detection, potentially reducing reliance on sprawling toolsets

AI-powered security reduces mean time to detect (MTTD) and mean time to respond (MTTR) significantly. 96% of cybersecurity professionals agree AI can meaningfully improve speed and efficiency, led by anomaly detection (72%) and automated response (48%).

Innov8World, 2026

Kiteworks AI Report, 2026

PRO ↓

AI enables platform consolidation, shrinking the number of security tools needed

55% of enterprises will accelerate consolidation driven by security drift and rising overheads. Integrated GenAI could cut employee-driven incidents by 40% when paired with a platform approach. 93% of security pros now favor integrated platforms over point products.

Computer Weekly, 2026

Kiteworks AI Report, 2026

PRO ↓

AI can close the cybersecurity skills gap, reducing need for expansive managed services

67% of organizations report a moderate-to-critical cybersecurity skills gap. AI-driven automation could partially compensate by handling routine monitoring, freeing teams from needing as many dedicated security platforms.

Hughes / WEF Outlook, 2026

PRO ↓

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AI is enabling "architecture-level redesign" of security. As AI-native platforms mature, functions like Zero Trust enforcement, traffic inspection, and policy management — core to SASE — could be absorbed into unified AI-first systems.

Innov8World, 2026

CON ↑

AI dramatically expands the attack surface, requiring more security coverage

AI agents act across systems, manage non-human identities, and make changes at machine speed — they "do not fit neatly into traditional access models." In 2026, machines and agents already outnumber human employees by an 82-to-1 ratio, all requiring governance.

CSA / Cloud Security Alliance, 2026

HBR / Palo Alto Networks, 2025

CON ↑

AI-powered attacks are outpacing defenses, making SASE more critical, not less

72% of organizations report increased cyber risk since 2024. Ransomware appeared in 44% of breaches in 2025 — a 37% increase year-over-year. AI-driven attacks adapt in real time, meaning fragmented stacks "simply can't keep up."

Hughes / WEF, 2026

Computer Weekly, 2026

CON ↑

"Shadow AI" usage by employees creates new data governance gaps SASE must fill

SASE is now positioned as a control point for governing AI usage — whitelisting approved tools, blocking risky ones, applying prompt-level DLP. Employees using "hundreds of long-tail niche AI services" and AI features embedded in approved SaaS apps cannot be governed without SASE-like brokering.

SC World / Check Point, 2026

CON ↑

SASE market is growing strongly, not contracting — AI is a driver, not a disruptor of demand

SASE is growing at a solid double-digit rate. Security SaaS overall is expected to grow from $17.4B in 2025 to $33.8B by 2030. Dell'Oro expects enterprises to budget more for SASE/SSE and less for legacy appliances through 2026 and beyond.

Network World / Dell'Oro, 2026

GII Research, 2026

CON ↑

AI agents require new SASE capabilities, expanding rather than replacing the platform

Cisco announced "AI-aware SASE" in February 2026, adding MCP visibility, intent-aware inspection of agentic interactions, and AI traffic optimization — none of which existed in traditional SASE. AI is forcing SASE to grow, not shrink.

Cisco Live EMEA, Feb 2026

CON ↑

Organizations are already breached at near-universal rates despite having 13+ tools — AI raises stakes further

99.4% of CISOs reported at least one SaaS or AI security incident in 2025. Organizations average 13 dedicated security tools yet feel unprotected. 86.8% plan to increase SaaS security budgets and 84.2% plan to increase AI security budgets in 2026.

GlobeNewswire / Vorlon, Mar 2026


As sometimes happens, market analysts and financial analysts tend to disagree, for reasons related to business models. 


Large market researchers are paid by vendors and suppliers who buy research subscriptions, commission custom reports, and pay for placement in analyst programs. 


Enterprise buyers also subscribe, but vendors are typically the bigger revenue source and the more active relationship.


The resulting biases:

  • Market size inflation. A large total addressable market forecast makes a vendor's pitch deck look compelling, justifies investment in the space, and makes the analyst firm look like it spotted a major trend early. There is almost no commercial downside to a bullish forecast, as nobody fires their Gartner subscription because a market grew slower than predicted. Forecasts are inherently unauditable in the short run, and by the time they're proven wrong, a new forecast has replaced them.

  • “New” markets and categories create buyer demand. When a vendor wants to differentiate their products, they often work closely with analyst firms to define and name a new category. The vendor gets a category it conveniently leads; the analyst firm gets cited as the authoritative source of the framework. The bias is toward proliferating categories rather than consolidating them, because each new category is a new revenue opportunity.

  • Optimistic adoption curves. Researchers consistently underestimate the friction of enterprise adoption. Their models tend to treat "total addressable market" as if it were "realistically serviceable market in the next three years," producing forecasts that flatter suppliers' sales projections.

  • Vendor-funded research. Commissioned studies. where a vendor pays for research that it then cites, are structurally compromised. The findings rarely bite the hand that feeds. 


Financial analysts (Sell-Side and Buy-Side) have different revenue models. Sell-side analysts at investment banks are ultimately paid through trading commissions and investment banking relationships (equity research is largely a loss leader that supports deal flow). 


The resulting biases:

  • Structural bullishness on covered stocks. Issuing a Sell on a company damages the relationship with that company's management, threatens future access to executives, and risks losing investment banking business. This means technology assessments of publicly traded companies are systematically skewed upward.

  • Recency and momentum bias. Analysts are rewarded for being right in the near term. A technology with strong recent earnings will get upgraded; one stumbling will get downgraded.

  • Narrative over fundamentals during hype cycles. Missing a major rally in a sector you cover is more career-damaging than being wrong alongside everyone else. This produces herd behavior..

  • Coverage selection bias. Analysts choose what to cover, and they tend to cover companies where there's trading volume and banking opportunity. Small, potentially disruptive competitors often go uncovered until they're large enough to matter.


Market researchers inflate the supply-side opportunity (how big is the market, how fast will it grow). 


Financial analysts inflate the demand-side story (which incumbent captures value). 


Market researchers tend to see AI as an unambiguous expansion of the enterprise technology market. Their instinct is additive and are structurally inclined to frame AI as a rising tide.


Financial analysts face a much harder problem, because AI introduces several simultaneous dynamics that are deeply ambiguous for incumbent valuations:

  • Commoditization risk: If AI compresses the differentiation between enterprise software products, then the moats that justified premium multiples erode

  • Capex displacement (some categories might shrink as others grow)

  • Margin uncertainty

  • Value uncertainty (will value for app-layer firms be threatened by alternatives?)


Market researchers tend to view AI as more incumbent friendly, where financial analysts see more threats to traditional seat license revenue models, for example. 


So one might argue market researchers are looking at “how much is being spent” where financial analysts are looking at “who captures the value?”


Either way, there is huge uncertainty about the “right” level of valuation for enterprise software firms.


Sunday, March 29, 2026

"Soak the Rich" is a Truly Dumb Idea, if a Catchy Slogan

Some of us dislike shallow or “bumper sticker slogan” levels of thinking. Economies and societies are very complicated things and we are very bad at understanding all the cause-and-effect interactions from any single public policy, as well intentioned as we might hope to be. 


Consider the oft-repeated desire to enhance societal fairness by taxation policies that “soak the rich (income or wealth, though income normally gets more attention).” To be fair, some countries do so, even if others have tried and failed to see revenue gains. 


If governments need revenue, why not take more from those who have the most? After all, some might argue, that’s why we have a progressive tax system (the tax rate increases as an individual's or entity's taxable income rises) in the first place. 


One might take the same approach to taxing wealth, though that is even more problematic. Perhaps you have read William Hinton’s Fanshen about the social revolutions attempted in a single Chinese village from 1945 to 1948. They took the “soak the rich” approach to wealth. 


Basically, what they discovered is that expropriating all the tangible wealth of the wealthy did not help. 


Land reform was a success in destroying the old social order and empowering the poor politically, but did not solve the deep economic problems in rural China. 


“Soak the rich” (usually phrased as “pay your fair share”) sounds good to many. But it hasn’t worked where it has been tried, simply because capital is mobile.


High-net-worth individuals have the means to move to lower-tax jurisdictions with relative ease:

  • France's 2012 supertax of 75 percent on incomes over €1 million saw a well-publicized wave of departures and was quietly abandoned after just two years having raised far less than projected

  • Sweden, which once had some of the world's highest marginal rates and a wealth tax, saw significant capital flight and eventually *cut* taxes substantially, including abolishing its wealth tax entirely in 2007, after concluding the tax was destroying more value than it captured

  • The UK's 50percent top rate introduced in 2010 was found by HMRC's own analysis to have raised little net revenue; it was reduced to 45percent in 2013

  • Some times a one percent increase causes capital flight. 


Asset restructuring also happens. Wealthy individuals employ armies of accountants and attorneys whose entire professional purpose is legal tax minimization. 


Higher marginal rates also reduce the incentive to take on additional risk, start new ventures, or work additional hours. This effect is debated in magnitude, but virtually no serious economist argues it is zero. 


All of these dynamics are captured in the concept of the “Laffer Curve.” There is some tax rate above which additional increases actually reduce total revenue.


Economists debate fiercely where that peak rate sits, with estimates ranging from roughly 50 percent to 70 percent for top marginal income tax rates. 


But set that all aside. Using the United States as an example, what would be the potential impact if none of the above actually happened?


If the government literally confiscated all the income of the top one percent of filers:

  • Any benefit is gained but once

  • Confiscating all the wealth of the Forbes 400 would fund the federal government for less than one year, and again, only once

  • A two-percent annual wealth tax on fortunes over $50 million might raise $200–300 billion per year, a single-digit portion of the federal deficit, at best

  • A 70-percent top marginal income tax rate might raise $50 and $300 billion per year, less than five percent of federal spending.


The fundamental arithmetic problem is that there are not enough “one percent” payers or even “top-10-percent payers” to fund a large modern welfare state.


Wealth taxes have been tried and abandoned by Germany, Sweden, France, Finland, Iceland, and others. Even if no behavioral changes occurred, low single digit rates of revenue increase are about the best we might expect to see from a one-percent wealth tax.


And even Switzerland, with a high payer base and low rates for its wealth tax, only generates about three percent of total tax revenue from that source. 


Confiscatory policies cause behavioral changes by the wealthy, gaming the system in lawful ways.  


But even in a fantasy scenario of zero behavioral response and total compliance, the additional revenue from hyper-progressive taxation on the wealthy would make only a modest dent in the fiscal gaps of large modern governments. 


The numbers simply aren't big enough relative to the scale of government spending. There aren't enough rich people.

source: The Tax Foundation


The point is, simple sound bites, catchy slogans and concise bumper stickers are not a substitute for actual thinking about whether policies actually can work. 


“Soak the rich” income or wealth tax policies fall neatly into those categories. They might make you feel good, but do not work in the real world to the extent you might imagine.


Buddhist and Christian Takes on "Suffering"

Being as how it is Holy Week for Christians, and focused (for some) on the passion (from Latin passio, "suffering"), or intense ph...